Main Reference PaperEfficient Computation of Robust Average of Compressive Sensing Data in Wireless Sensor Networks in the Presence of Sensor Faults, IEEE Transactions on Parallel and Distributed Systems, Aug 2013.
  • An effective computation method is provided to compute a weighted average for sensors nodes, which also takes takes sensor faults andsensor noise.The sensors in the network use random projections to compress the data and send the compressed data to the data fusion centre. In proposed work , the data fusion centre only needs to perform decompression once to compute the robust average, thus greatly reducing the computational cost.

+ Description
  • An effective computation method is provided to compute a weighted average for sensors nodes, which also takes takes sensor faults andsensor noise.The sensors in the network use random projections to compress the data and send the compressed data to the data fusion centre. In proposed work , the data fusion centre only needs to perform decompression once to compute the robust average, thus greatly reducing the computational cost.

  • Achieve the Computational efficiency

  • Reducing computation cost.

+ Aim & Objectives
  • Achieve the Computational efficiency

  • Reducing computation cost.

  • A technique is contributed to further reduce the computation cost and improve the robust average of compressive data.

+ Contribution
  • A technique is contributed to further reduce the computation cost and improve the robust average of compressive data.

  • OS : Window 7 (Cygwin) / Ubuntu 12.04 LTS 64bit.

  • Simulator: NS 2.35, Language : TCL and AWK script, (C++)

+ Software Tools & Technologies
  • OS : Window 7 (Cygwin) / Ubuntu 12.04 LTS 64bit.

  • Simulator: NS 2.35, Language : TCL and AWK script, (C++)

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

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